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Dataset summary: Dengue - grouped by patient¶

Report generated using dataprep.

Dengue dataset report

Overview

Dataset Statistics

Number of Variables	14
Number of Rows	14484
Missing Cells	0
Missing Cells (%)	0.0%
Duplicate Rows	32
Duplicate Rows (%)	0.2%
Total Size in Memory	3.3 MB
Average Row Size in Memory	235.4 B

Variable Types

Categorical	9
Numerical	5

Variables

dsource

categorical

Distinct Count	10
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory Size	1.7 MB

Stats Plots

Length

Mean	3.1826
Standard Deviation	0.9882
Median	4
Minimum	2
Maximum	5

Sample

1st row	01nva
2nd row	01nva
3rd row	01nva
4th row	01nva
5th row	01nva

Letter

Count	28967
Lowercase Letter	28967
Space Separator	0
Uppercase Letter	0
Dash Punctuation	0
Decimal Number	17130

age

numerical

Distinct Count	27
Unique (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Memory Size	1.0 MB
Mean	8.2995
Minimum	0
Maximum	18
Zeros	4
Zeros (%)	0.0%
Negatives	0
Negatives (%)	0.0%

Stats Plots

Quantile Statistics

Minimum	0
5-th Percentile	2
Q1	5
Median	8
Q3	11
95-th Percentile	14
Maximum	18
Range	18
IQR	6

Descriptive Statistics

Mean	8.2995
Standard Deviation	3.9859
Variance	15.8876
Sum	120210.5
Skewness	-0.02044
Kurtosis	-0.8352
Coefficient of Variation	0.4803

gender

categorical

Distinct Count	2
Unique (%)	0.0%
Missing	0
Missing (%)	0.0%
Memory Size	1.8 MB

Stats Plots

Length

Mean	4.8737
Standard Deviation	0.992
Median	4
Minimum	4
Maximum	6

Sample

1st row	Male
2nd row	Female
3rd row	Female
4th row	Male
5th row	Female

Letter

Count	70590
Lowercase Letter	56106
Space Separator	0
Uppercase Letter	14484
Dash Punctuation	0
Decimal Number	0

weight

numerical

Distinct Count	353
Unique (%)	2.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Memory Size	1.0 MB
Mean	28.4854
Minimum	7.2
Maximum	114
Zeros	0
Zeros (%)	0.0%
Negatives	0
Negatives (%)	0.0%

Stats Plots

Quantile Statistics

Minimum	7.2
5-th Percentile	12
Q1	19
Median	26
Q3	37
95-th Percentile	52
Maximum	114
Range	106.8
IQR	18

Descriptive Statistics

Mean	28.4854
Standard Deviation	12.8
Variance	163.8408
Sum	412582.6
Skewness	0.8739
Kurtosis	0.8789
Coefficient of Variation	0.4494

bleeding

categorical

Distinct Count	2
Unique (%)	0.0%
Missing	0
Missing (%)	0.0%
Memory Size	1.8 MB

Stats Plots

Length

Mean	4.7429
Standard Deviation	0.4371
Median	5
Minimum	4
Maximum	5

Sample

1st row	True
2nd row	False
3rd row	True
4th row	False
5th row	False

Letter

Count	68696
Lowercase Letter	54212
Space Separator	0
Uppercase Letter	14484
Dash Punctuation	0
Decimal Number	0

plt

numerical

Distinct Count	1144
Unique (%)	7.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Memory Size	1.0 MB
Mean	167.1835
Minimum	3
Maximum	829
Zeros	0
Zeros (%)	0.0%
Negatives	0
Negatives (%)	0.0%

Stats Plots

Quantile Statistics

Minimum	3
5-th Percentile	24
Q1	71
Median	169
Q3	243
95-th Percentile	338
Maximum	829
Range	826
IQR	172

Descriptive Statistics

Mean	167.1835
Standard Deviation	104.5549
Variance	10931.7272
Sum	2.4215e+06
Skewness	0.4243
Kurtosis	-0.1921
Coefficient of Variation	0.6254

shock

categorical

Distinct Count	2
Unique (%)	0.0%
Missing	0
Missing (%)	0.0%
Memory Size	1.8 MB

Stats Plots

Length

Mean	4.9516
Standard Deviation	0.2146
Median	5
Minimum	4
Maximum	5

Sample

1st row	True
2nd row	True
3rd row	True
4th row	True
5th row	True

Letter

Count	71719
Lowercase Letter	57235
Space Separator	0
Uppercase Letter	14484
Dash Punctuation	0
Decimal Number	0

haematocrit_percent

numerical

Distinct Count	560
Unique (%)	3.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Memory Size	1.0 MB
Mean	41.3015
Minimum	21
Maximum	67.05
Zeros	0
Zeros (%)	0.0%
Negatives	0
Negatives (%)	0.0%

Stats Plots

Quantile Statistics

Minimum	21
5-th Percentile	33.5
Q1	37.2
Median	40.3
Q3	45
95-th Percentile	52
Maximum	67.05
Range	46.05
IQR	7.8

Descriptive Statistics

Mean	41.3015
Standard Deviation	5.6372
Variance	31.7783
Sum	598210.2593
Skewness	0.6312
Kurtosis	0.1445
Coefficient of Variation	0.1365

bleeding_gum

categorical

Distinct Count	2
Unique (%)	0.0%
Missing	0
Missing (%)	0.0%
Memory Size	1.8 MB

Stats Plots

Length

Mean	4.8903
Standard Deviation	0.3125
Median	5
Minimum	4
Maximum	5

Sample

1st row	True
2nd row	False
3rd row	True
4th row	False
5th row	False

Letter

Count	70831
Lowercase Letter	56347
Space Separator	0
Uppercase Letter	14484
Dash Punctuation	0
Decimal Number	0

abdominal_pain

categorical

Distinct Count	2
Unique (%)	0.0%
Missing	0
Missing (%)	0.0%
Memory Size	1.8 MB

Stats Plots

Length

Mean	4.682
Standard Deviation	0.4657
Median	5
Minimum	4
Maximum	5

Sample

1st row	True
2nd row	True
3rd row	True
4th row	True
5th row	True

Letter

Count	67814
Lowercase Letter	53330
Space Separator	0
Uppercase Letter	14484
Dash Punctuation	0
Decimal Number	0

ascites

categorical

Distinct Count	2
Unique (%)	0.0%
Missing	0
Missing (%)	0.0%
Memory Size	1.8 MB

Stats Plots

Length

Mean	4.8391
Standard Deviation	0.3675
Median	5
Minimum	4
Maximum	5

Sample

1st row	False
2nd row	False
3rd row	False
4th row	False
5th row	False

Letter

Count	70089
Lowercase Letter	55605
Space Separator	0
Uppercase Letter	14484
Dash Punctuation	0
Decimal Number	0

bleeding_mucosal

categorical

Distinct Count	2
Unique (%)	0.0%
Missing	0
Missing (%)	0.0%
Memory Size	1.8 MB

Stats Plots

Length

Mean	4.8159
Standard Deviation	0.3876
Median	5
Minimum	4
Maximum	5

Sample

1st row	False
2nd row	False
3rd row	True
4th row	False
5th row	False

Letter

Count	69754
Lowercase Letter	55270
Space Separator	0
Uppercase Letter	14484
Dash Punctuation	0
Decimal Number	0

bleeding_skin

categorical

Distinct Count	2
Unique (%)	0.0%
Missing	0
Missing (%)	0.0%
Memory Size	1.8 MB

Stats Plots

Length

Mean	4.5429
Standard Deviation	0.4982
Median	5
Minimum	4
Maximum	5

Sample

1st row	False
2nd row	False
3rd row	True
4th row	False
5th row	False

Letter

Count	65800
Lowercase Letter	51316
Space Separator	0
Uppercase Letter	14484
Dash Punctuation	0
Decimal Number	0

body_temperature

numerical

Distinct Count	1218
Unique (%)	8.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Memory Size	1.0 MB
Mean	37.8323
Minimum	35
Maximum	41.5
Zeros	0
Zeros (%)	0.0%
Negatives	0
Negatives (%)	0.0%

Stats Plots

Quantile Statistics

Minimum	35
5-th Percentile	37
Q1	37.2
Median	37.58
Q3	38.3333
95-th Percentile	39.5
Maximum	41.5
Range	6.5
IQR	1.1333

Descriptive Statistics

Mean	37.8323
Standard Deviation	0.8257
Variance	0.6818
Sum	547963.5822
Skewness	0.9208
Kurtosis	0.2582
Coefficient of Variation	0.02183

Interactions

Correlations

Missing Values

 import pandas as pd
 import numpy as np
 from dataprep.eda import create_report
 from pkgname.utils.data_loader import load_dengue, IQR_rule
 from pkgname.utils.print_utils import suppress_stdout, suppress_stderr

 features = ["dsource", "age", "gender", "weight", "bleeding", "plt",
             "shock", "haematocrit_percent", "bleeding_gum", "abdominal_pain",
             "ascites", "bleeding_mucosal", "bleeding_skin", "body_temperature"]

 with suppress_stdout() and suppress_stderr():

     df = load_dengue(usecols=['study_no']+features)

     for feat in features:
         df[feat] = df.groupby('study_no')[feat].ffill().bfill()

     df = df.loc[df['age'] <= 18]
     df = df.dropna()

     df = df.groupby(by="study_no", dropna=False).agg(
         dsource=pd.NamedAgg(column="dsource", aggfunc="last"),
         age=pd.NamedAgg(column="age", aggfunc="max"),
         gender=pd.NamedAgg(column="gender", aggfunc="first"),
         weight=pd.NamedAgg(column="weight", aggfunc=np.mean),
         bleeding=pd.NamedAgg(column="bleeding", aggfunc="max"),
         plt=pd.NamedAgg(column="plt", aggfunc="min"),
         shock=pd.NamedAgg(column="shock", aggfunc="max"),
         haematocrit_percent=pd.NamedAgg(column="haematocrit_percent", aggfunc="max"),
         bleeding_gum=pd.NamedAgg(column="bleeding_gum", aggfunc="max"),
         abdominal_pain=pd.NamedAgg(column="abdominal_pain", aggfunc="max"),
         ascites=pd.NamedAgg(column="ascites", aggfunc="max"),
         bleeding_mucosal=pd.NamedAgg(column="bleeding_mucosal", aggfunc="max"),
         bleeding_skin=pd.NamedAgg(column="bleeding_skin", aggfunc="max"),
         body_temperature=pd.NamedAgg(column="body_temperature", aggfunc=np.mean),
     ).dropna()

     df = IQR_rule(df, ['plt'])

     report = create_report(df, title="Dengue dataset report")

 report

Total running time of the script: ( 0 minutes 5.308 seconds)

Download Python source code: plot_data_summary_dengue_grouped.py

Download Jupyter notebook: plot_data_summary_dengue_grouped.ipynb

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